Three Dimension Face Recognition Based on Gabor Transformation and Support Vector Machine

Face recognition based on 2D face images is still challenged by the large change of illumination, pose and expression after more than 10 year's research and its recognition rate is still far away from satisfaction under the change of the above three factors. Gabor wavelet and support vector machine (SVM) are studied. Gabor wavelet has good biological neurons function, and good adaptive change to illumination. Furthermore, SVM can provide good classification effect. Gabor wavelet and SVM are combined with PCA to improve recognition rate of human face. Besides, we put forward a kind of Gabor wavelet feature extraction method based on three-dimensional human face contour line. Five different types of human face recognition are used to verify the effectiveness of this algorithm. The experiment results show that the proposed scheme has higher recognition rate than several traditional schemes.